<!DOCTYPE html>
<html lang="en">
<head>
<meta http-equiv="content-type" content="text/html; charset=utf-8" name="description" content="GPTIPS 2 pareto report" name="author" content="Dominic Searson"/>
<title>GPTIPS pareto front report.</title>
<script type="text/javascript" src="http://www.google.com/jsapi"></script>
<script type="text/javascript">google.load('visualization', '1', {packages: ['table']});
</script>
<link href='http://fonts.googleapis.com/css?family=Open+Sans' rel='stylesheet' type='text/css'>
<style>
h1, h2, h3 {
color: #0073bd; margin-top: 20px; 
}
p.warn {
color: #993300; 
}
.google-visualization-table-table .google-visualization-table-td-number {
font-family: 'Open Sans','Helvetica Neue', Helvetica, Arial, sans-serif;text-align: left;
}
.google-visualization-table-td {
padding-top: 6px;padding-bottom: 6px;font-size: 14px;
}
</style>
<script type="text/javascript">
function drawPerformanceTable() {
var data = new google.visualization.DataTable();
data.addColumn('number','Model ID');
data.addColumn('number','Goodness of fit (R<sup>2</sup>)');
data.addColumn('number','Model complexity');
data.addColumn('string','Model');
data.addRows(15);
data.setCell(0,0, 1);
data.setCell(0,1, 0.916);
data.setCell(0,2, 194);
data.setCell(0,3, '1.14 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) - 14.4 normals_3 - 6.61 lightdir_3 + 0.912 sin(tan(normals_2)) - 6.04e-5 tan(lightdir_3 + normals_3 + sin(lightdir_2)) - 0.00578 tan(tan(lightdir_3 - 1.0 normals_3)) + 7.04 sin(sin(sin(normals_3))) - 7.75 cos(lightdir_3) - 65.3 cos(0.289 lightdir_2 + 0.289 normals_3) - 7.59e-5 tan(sin(lightdir_2) + 4.13) + 9.5 lightdir_2 lightdir_3 + 1.14 lightdir_2 normals_3 - 0.912 lightdir_2 tan(normals_2) - 9.5 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> - 13.0 lightdir_2 sin(lightdir_2) sin(normals_3) + 13.0 lightdir_3 sin(lightdir_2) sin(normals_3) + 73.1');
data.setCell(1,0, 7);
data.setCell(1,1, 0.916);
data.setCell(1,2, 186);
data.setCell(1,3, '0.601 lightdir_2 - 6.94 lightdir_3 - 14.5 normals_3 + 0.601 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) + 1.02 sin(tan(normals_2)) - 5.94e-5 tan(lightdir_3 + normals_3 + sin(lightdir_2)) - 0.00587 tan(tan(lightdir_3 - 1.0 normals_3)) + 7.69 sin(sin(sin(normals_3))) - 7.54 cos(lightdir_3) - 72.3 cos(0.289 lightdir_2 + 0.289 normals_3) - 7.49e-5 tan(sin(lightdir_2) + 4.13) + 10.1 lightdir_2 lightdir_3 - 1.02 lightdir_2 tan(normals_2) - 10.1 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> - 11.8 lightdir_2 sin(lightdir_2) sin(normals_3) + 11.8 lightdir_3 sin(lightdir_2) sin(normals_3) + 79.9');
data.setCell(2,0, 23);
data.setCell(2,1, 0.913);
data.setCell(2,2, 180);
data.setCell(2,3, '3.43 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) - 4.77 normals_3 - 0.669 lightdir_3 - 1.13 sin(tan(normals_2)) - 7.49e-5 tan(lightdir_3 + normals_3 + sin(lightdir_2)) - 0.00496 tan(tan(lightdir_3 - 1.0 normals_3)) + 1.45 sin(sin(sin(normals_3))) + 7.68 cos(lightdir_2) - 4.1 cos(lightdir_3) - 8.85e-5 tan(sin(lightdir_2) + 4.13) - 0.499 lightdir_2 lightdir_3 + 3.43 lightdir_2 normals_3 + 1.13 lightdir_2 tan(normals_2) + 0.499 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> - 7.43 lightdir_2 sin(lightdir_2) sin(normals_3) + 7.43 lightdir_3 sin(lightdir_2) sin(normals_3) - 3.58');
data.setCell(3,0, 30);
data.setCell(3,1, 0.915);
data.setCell(3,2, 183);
data.setCell(3,3, '0.936 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) - 14.2 normals_3 - 6.62 lightdir_3 + 0.961 sin(tan(normals_2)) - 0.00574 tan(tan(lightdir_3 - 1.0 normals_3)) + 8.01 sin(sin(sin(normals_3))) - 1.52 tan(sin(sin(normals_3))) - 7.56 cos(lightdir_3) - 72.0 cos(0.289 lightdir_2 + 0.289 normals_3) - 7.4e-5 tan(sin(lightdir_2) + 4.13) + 9.79 lightdir_2 lightdir_3 + 0.936 lightdir_2 normals_3 - 0.961 lightdir_2 tan(normals_2) - 9.79 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> - 13.6 lightdir_2 sin(lightdir_2) sin(normals_3) + 13.6 lightdir_3 sin(lightdir_2) sin(normals_3) + 79.6');
data.setCell(4,0, 46);
data.setCell(4,1, 0.873);
data.setCell(4,2, 110);
data.setCell(4,3, '0.624 lightdir_3 + 0.624 normals_3 + 0.624 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) - 4.34e-5 tan(lightdir_3 + normals_3 + sin(lightdir_2)) + 1.5 sin(sin(sin(normals_3))) + 18.1 cos(0.289 lightdir_2 + 0.289 normals_3) - 6.68e-5 tan(sin(lightdir_2) + 4.13) - 0.461 lightdir_2 lightdir_3 + 0.624 lightdir_2 normals_3 + 0.461 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> - 18.1');
data.setCell(5,0, 76);
data.setCell(5,1, 0.916);
data.setCell(5,2, 190);
data.setCell(5,3, '1.44 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) - 14.9 normals_3 - 6.73 lightdir_3 + 7.92 sin(sin(normals_3)) + 0.908 sin(tan(normals_2)) - 6.09e-5 tan(lightdir_3 + normals_3 + sin(lightdir_2)) - 0.00587 tan(tan(lightdir_3 - 1.0 normals_3)) - 8.17 cos(lightdir_3) - 57.6 cos(0.289 lightdir_2 + 0.289 normals_3) - 7.64e-5 tan(sin(lightdir_2) + 4.13) + 9.27 lightdir_2 lightdir_3 + 1.44 lightdir_2 normals_3 - 0.908 lightdir_2 tan(normals_2) - 9.27 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> - 12.4 lightdir_2 sin(lightdir_2) sin(normals_3) + 12.4 lightdir_3 sin(lightdir_2) sin(normals_3) + 65.7');
data.setCell(6,0, 105);
data.setCell(6,1, 0.9);
data.setCell(6,2, 119);
data.setCell(6,3, '0.0711 lightdir_3 - 0.373 normals_3 + 0.515 sin(lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) - 5.69e-5 tan(lightdir_3 + normals_3 + sin(lightdir_2)) - 0.00584 tan(tan(lightdir_3 - 1.0 normals_3)) - 0.444 cos(lightdir_3) - 7.96e-5 tan(sin(lightdir_2) + 4.13) + 1.68 lightdir_2 lightdir_3 + 0.515 lightdir_2 normals_3 - 1.68 lightdir_2<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span> + 0.444');
data.setCell(7,0, 341);
data.setCell(7,1, 0.912);
data.setCell(7,2, 164);
data.setCell(7,3, '0.105 tan(tan(lightdir_2 + 4.84)) + 38.8 cos((2500.0 tan(lightdir_2))/(2500.0 lightdir_2 + 1.12e4)) + 2.0e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 1.94 sin(0.396 normals_3) - 0.00578 tan(tan(lightdir_3 - 1.0 normals_3)) + (3.33e17 tan(lightdir_2))/(8.8e16 lightdir_2 + 3.91e17) + (3.33e17 lightdir_2)/(8.8e16 lightdir_2 + 3.89e17) - (1.44e-5 normals_3 (5000.0 tan(lightdir_2) + 4.8e4))/cos(normals_1) - 38.4');
data.setCell(8,0, 371);
data.setCell(8,1, 0.918);
data.setCell(8,2, 216);
data.setCell(8,3, '0.106 tan(tan(lightdir_2 + 4.84)) + 61.0 cos((2500.0 tan(lightdir_2))/(2500.0 lightdir_2 + 1.12e4)) - 5.29e-4 tan(normals_3 + tan(lightdir_2) + 10.2) + 1.94e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 4.03e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 116.0 sin(0.396 normals_3) - 0.00525 tan(tan(lightdir_3 - 1.0 normals_3)) + (2.83e18 tan(lightdir_2))/(1.76e17 lightdir_2 + 7.46e17) - 1.0e-33 lightdir_2 (5.08e33 lightdir_3 - 1.02e34 normals_3 + 4.6e32 lightdir_3 normals_3 - 9.2e32 normals_3<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) + (2.83e18 lightdir_2)/(1.76e17 lightdir_2 + 7.79e17) - (0.001 normals_3 (5000.0 tan(lightdir_2) + 4.8e4))/cos(normals_1) - 60.5');
data.setCell(9,0, 372);
data.setCell(9,1, 0.917);
data.setCell(9,2, 196);
data.setCell(9,3, '0.0185 lightdir_3 + 0.106 tan(tan(lightdir_2 + 4.84)) + 58.5 cos((1.0e4 tan(lightdir_2))/(1.0e4 lightdir_2 + 4.43e4)) - 5.4e-4 tan(normals_3 + tan(lightdir_2) + 10.2) + 4.05e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 116.0 sin(0.396 normals_3) - 0.00527 tan(tan(lightdir_3 - 1.0 normals_3)) + (3.59e17 tan(lightdir_2))/(2.2e16 lightdir_2 + 9.77e16) - 2.0e-33 lightdir_2 (2.54e33 lightdir_3 - 5.08e33 normals_3 + 2.3e32 lightdir_3 normals_3 - 4.6e32 normals_3<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) + (3.59e17 lightdir_2)/(2.2e16 lightdir_2 + 9.73e16) - (0.001 normals_3 (5000.0 tan(lightdir_2) + 4.8e4))/cos(normals_1) - 58.1');
data.setCell(10,0, 377);
data.setCell(10,1, 0.918);
data.setCell(10,2, 212);
data.setCell(10,3, '0.105 tan(tan(lightdir_2 + 4.84)) + 60.5 cos((2500.0 tan(lightdir_2))/(2500.0 lightdir_2 + 1.12e4)) - 5.29e-4 tan(normals_3 + tan(lightdir_2) + 10.2) + 1.94e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 4.03e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 116.0 sin(0.396 normals_3) - 0.00525 tan(tan(lightdir_3 - 1.0 normals_3)) - 5.01 normals_3 (tan(lightdir_2) + 9.59) + (2.89e18 tan(lightdir_2))/(1.76e17 lightdir_2 + 7.82e17) - 1.0e-33 lightdir_2 (5.08e33 lightdir_3 - 1.02e34 normals_3 + 4.6e32 lightdir_3 normals_3 - 9.2e32 normals_3<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) + (2.89e18 lightdir_2)/(1.76e17 lightdir_2 + 7.79e17) - 60.1');
data.setCell(11,0, 421);
data.setCell(11,1, 0.841);
data.setCell(11,2, 100);
data.setCell(11,3, '0.0177 tan(tan(lightdir_2 + 4.84)) + 2.96e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 4.05 sin(0.396 normals_3) + 0.0484 lightdir_2 (normals_3 + 11.0) (lightdir_3 - 2.0 normals_3) + 0.0721');
data.setCell(12,0, 425);
data.setCell(12,1, 0.911);
data.setCell(12,2, 129);
data.setCell(12,3, '0.104 tan(tan(lightdir_2 + 4.84)) + 38.5 cos((2500.0 tan(lightdir_2))/(2500.0 lightdir_2 + 1.12e4)) + 2.2 sin(0.396 normals_3) - 0.00579 tan(tan(lightdir_3 - 1.0 normals_3)) - 0.0818 normals_3 (tan(lightdir_2) + 9.59) + (5.31e18 tan(lightdir_2))/(1.41e18 lightdir_2 + 6.25e18) + (5.31e18 lightdir_2)/(1.41e18 lightdir_2 + 6.23e18) - 38.1');
data.setCell(13,0, 474);
data.setCell(13,1, 0.917);
data.setCell(13,2, 208);
data.setCell(13,3, '1.01e-4 tan(tan(lightdir_2) + 9.59) + 0.104 tan(tan(lightdir_2 + 4.84)) + 60.2 cos((2500.0 tan(lightdir_2))/(2500.0 lightdir_2 + 1.12e4)) - 5.4e-4 tan(normals_3 + tan(lightdir_2) + 10.2) + 4.04e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 116.0 sin(0.396 normals_3) - 0.00526 tan(tan(lightdir_3 - 1.0 normals_3)) + (2.89e18 tan(lightdir_2))/(1.76e17 lightdir_2 + 7.82e17) - 1.0e-33 lightdir_2 (5.08e33 lightdir_3 - 1.02e34 normals_3 + 4.6e32 lightdir_3 normals_3 - 9.21e32 normals_3<span style="position:relative;bottom: 0.3em;font-size:0.7em">2</span>) + (2.89e18 lightdir_2)/(1.76e17 lightdir_2 + 7.79e17) - (0.00101 normals_3 (5000.0 tan(lightdir_2) + 4.8e4))/cos(normals_1) - 59.8');
data.setCell(14,0, 503);
data.setCell(14,1, 0.915);
data.setCell(14,2, 182);
data.setCell(14,3, '0.102 tan(tan(lightdir_2 + 4.84)) + 39.6 cos((2500.0 tan(lightdir_2))/(2500.0 lightdir_2 + 1.12e4)) - 5.11e-4 tan(normals_3 + tan(lightdir_2) + 10.2) + 1.94e-4 tan(normals_3 + tan(lightdir_2) + 10.3) + 4.04e-4 tan(normals_3 + tan(lightdir_2) + 10.3) - 0.00572 tan(tan(lightdir_3 - 1.0 normals_3)) + (2.71e18 tan(lightdir_2))/(7.04e17 lightdir_2 + 3.13e18) + (2.71e18 lightdir_2)/(7.04e17 lightdir_2 + 3.11e18) + 6.0e-36 lightdir_2 (lightdir_3 - 2.0 normals_3) (3.37e31 normals_3 + 3.72e32) - 39.2');
viz = new google.visualization.Table(document.getElementById('perf_table'));
viz.draw(data,  {width: 1000, allowHtml: true});}
google.setOnLoadCallback(drawPerformanceTable);
 </script>
</head>
<body>
<body style="font-family: 'Open Sans','Helvetica Neue', Helvetica, Arial, sans-serif; border: 0;">
<div style="text-align: left; margin-bottom: 50px;margin-top: 50px;margin-left: 15px;"><h2>GPTIPS pareto front report</h2><p>27-Jun-2016 21:34:37</p>
<p>Config file: symreg_config.m</p>
<p>Number of models on front: 15</p><p>Total models: 600</p><p style="margin-top: 30px;">This report shows the expressional complexity/performance characteristics (on training data) of symbolic models on the pareto front.</p><p>Numerical precision is reduced for display purposes.</p><p style="margin-bottom: 30px;">Click on column headers to sort models by expressional complexity and goodness of fit (R<sup>2</sup>).</p><div id="perf_table"></div>
<p style="color:gray;text-align:center;margin-top: 50px;">GPTIPS - the symbolic data mining platform for MATLAB</p><p style="color:gray;text-align:center;">&#169; Dominic Searson 2009-2015</p></div>
</body>
</html>
